Various automotive vehicles have recently begun including vehicle control systems. Such vehicle control systems include yaw stability control systems, roll stability control systems, integrated vehicle dynamic control systems, etc. The ongoing goal of vehicle controls is to achieve a coordinated system level vehicle performances for ride, handling, safety and fuel economy.
With current advances in mechatronics, vehicle controls have increased opportunities for achieving performances, which were previously reserved for spacecraft and aircraft. For example, gyro sensors, previously only used in aircraft, have now been incorporated in various vehicle controls, and the anti-lock brake systems invented for airplanes are now standard automotive control systems. Current sensor technology generates ever-increasing opportunities for vehicle control.
A typical vehicle control system utilizes 3-dimensional vehicle motions. For example, during yaw stability and roll stability controls, the control task involves three-dimensional motions along the vehicle roll, pitch, and yaw directions and along the vehicle longitudinal, lateral and vertical directions.
The coupling between different motion directions should not be neglected in most maneuvers involving vehicle roll over or vehicle yaw. For example, excessive steering of a vehicle will lead to excessive yaw and lateral motion, which may cause large rolling motion towards the outside of a turn. If the driver brakes the vehicle during the excessive steering, the vehicle will also experience roll and pitch motions in conjunction with lateral and longitudinal accelerations. Therefore, a successful vehicle dynamics control should involve an accurate determination of the vehicle roll, pitch and yaw attitudes (side slip angle).
Currently, inertial measurement units (IMUs) and various other sensors used in aerospace vehicle controls have been incorporated in automotive vehicles for inertial control. IMUs have been used in inertial navigation systems (INS) for aircrafts and satellites for decades. Typically, an INS system determines the attitude of a flight vehicle through IMU sensor signals.
An IMU sensor set includes three gyros and three linear accelerometers. An INS contains an IMU and a processor unit to compute the navigation solutions necessary for navigation, attitude reference and various other data communication sources.
Although INS systems are sufficient to generate a navigation solution, over time the computation based on IMU sensor signals drifts, and the errors associated with the computation increases. Sometimes these errors increase such that a navigation solution is unattainable within the INS. To mitigate this problem and to compute a correct navigation solution over the entire flight, external navigation sources are used to continually correct the attitude computations based on IMU sensor signals. One of the more reliable of external sources is a GPS system with multiple GPS receivers. Such a system has been used to determine a rough attitude reference of a vehicle in flight.
Current automotive vehicle systems experience a similar signal drift problem in vehicle attitude determination. Although the drift is not as severe as in aerospace vehicles, it generates errors within the vehicle control system such that the vehicle control system engages improper actions.
It would therefore be desirable to provide a vehicle system sensing algorithm that uses sensors to determine the vehicle operation states, to monitor abnormal vehicle operation states, and to compensate the sensor errors for various automotive vehicle control applications.